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dc.contributor.authorZerari, Nassira
dc.contributor.authorChemachema, Mohamed
dc.date.accessioned2021-03-23T14:00:00Z
dc.date.available2021-03-23T14:00:00Z
dc.date.issued2019-11-14
dc.identifier.urihttp://hdl.handle.net/123456789/136801
dc.description.abstractThe main objective of this thesis is the development of adaptive control laws for particular classes of uncertain SISO and MIMO nonlinear systems. The cases of the affine and non-affine systems, the presence of the constraints on the outputs and/or the states as well as the external perturbations are studied. Furthermore, the saturation and dead-zone inputs nonlinearities of the dynamical systems are investigated. In all the proposed approaches, the neural networks are used as universal approximators to estimate the unknown nonlinearities of the dynamical systems. The structures of the proposed controllers deal with the famous problems of explosion of complexity while avoiding the use of the traditional back-stepping technique. The proposed adaptive neural controllers have few online learning parameters compared to similar works. In addition, stability analysis of all control loops is carried out by using the Lyapunov method, and for each scheme, simulation results are given to show its effectiveness.fr_FR
dc.language.isofrfr_FR
dc.publisherجامعة الإخوة منتوري قسنطينةfr_FR
dc.subjectElectronique:Contrôle des systèmesfr_FR
dc.subjectRéseau de neuronesfr_FR
dc.subjectcommande adaptativefr_FR
dc.subjectsystèmes non linéairesfr_FR
dc.subjectsaturationfr_FR
dc.subjectzone-mortefr_FR
dc.subjectfonction de Nussbaumfr_FR
dc.subjectNeural networks (NNs)fr_FR
dc.subjectadaptive controlfr_FR
dc.subjectnonlinear systemsfr_FR
dc.subjectdead-zonefr_FR
dc.subjectNussbaum functionfr_FR
dc.subjectالشبكة العصبيةfr_FR
dc.subjectالتحكم تلاؤميfr_FR
dc.subjectأنظمة لاخطيةfr_FR
dc.subjectتشبعfr_FR
dc.subjectمنطقة ميتةfr_FR
dc.subjectدالة نيسبومfr_FR
dc.titleContribution à la commande adaptative robuste d’une classe de systèmes non linéaires.fr_FR
dc.typeThesisfr_FR


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